1. Field of Art
The present disclosure generally relates to the field of digital video, and more specifically, to training video classifiers to identify videos to allow for content claiming by content owners.
2. Background of the Invention
Video hosting services, such as YOUTUBE™, have become an increasingly popular way of sharing and viewing digital videos, with users contributing tens of millions of videos each year.
Some video hosting services use fingerprints or signatures to match uploaded videos to reference videos. Fingerprints are adequate to identify broadcast-type content because there exists a reference version of the broadcast content from which a reference fingerprint can be derived, and the content does not vary drastically between each copy or instance of the content. Examples of broadcast type content comprise official music videos, television content, movie content, broadcasted sports events etc. By comparing fingerprints of uploaded videos to fingerprints of reference videos, video hosting services may determine if a video matches a reference video.
However, it is difficult to develop fingerprints for content for which there is no reference version from which a reference fingerprint can be generated. One example of such content are videos of events that are captured from the point of view of the person participating or observing the event (referred to herein as “participant-observer videos” or “P/O videos”) because the content in the videos vary from video to video. This prevents video hosting services from identifying the source of the content included in P/O videos. For example, dozens of different users may create a video of particular concert (e.g., a content source), each taken from a different seat in the concert hall. While all of these videos are of the same event, each video is itself different from the other videos in its specific video and audio content. As a result, conventional fingerprinting methods would not identify these videos as matching.